A Temporal Stability Method for Improving Video Restoration by Integrating Multiple Regularization Methods

A video recovery and stability technology, applied in image enhancement, instruments, biological neural network models, etc., can solve problems such as unsatisfactory time domain stability of restoration results, flickering of adjacent frames, etc., to improve time domain stability , the effect of improving the robustness of the algorithm
CN111340740BActive Publication Date: 2021-01-15杭州微帧信息科技有限公司
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
杭州微帧信息科技有限公司
Publication Date
2021-01-15

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Abstract

The invention discloses a time-domain stability method for improving video restoration by integrating multiple regularization methods, and belongs to the technical field of video restoration. The method includes the following content: when using deep learning for video restoration, a common problem is that the images processed by a single frame are inconsistent in the time domain. robustness. Add the micro-transformation invariant regularization method, monochrome image regularization method, linear transformation consistent regularization method and secondary processing invariant loss regularization method to the CNN video restoration model, and optimize and adjust the loss function of the neural network through the above methods, A more robust video restoration model is obtained to solve the inconsistency problem in the temporal domain of single-frame processed images.
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Description

technical field

[0001] The present invention relates to the technical field of video restoration, in particular to a time-domain stability method for improving video restoration by integrating multiple regularization methods. Background technique

[0002] In recent years, with the development of the Internet and the popularity of smart terminals, images and videos have become the most commonly used information carriers in human activities. However, in the process of image acquisition, transmission, storage and processing, it will always be affected by various degradation factors, resulting in the degradation of image quality, which has a great impact on subsequent image understanding and use. Therefore, in order to obtain high To improve the image quality, it is necessary to restore the video image to keep the integrity of the original information as much as possible. Therefore, video restoration has always been a hot spot in image processing and computer vision research. ...

Claims

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